# Schedule ## expand\_more All of the papers should be available through google scholar. Logging into Harvard library should also make it easy to access these papers. ## Definitions, course structure: ### 1. (Jan 26) Lecture 1: Course intro, syllabus, goals, key concepts: Perspectives on AI in Society; overview. [Lecture 1 slides](/file_url/114) **Handout: Syllabus** ***Optional readings:*** - *L. Floridi, J.Cowles, T. King, M. Taddeo “*[*How to design AI for Social Good: Seven Essential Factors*](https://doi.org/10.1007/s11948-020-00213-5)*” Science and Engineering Ethics (2020) 26:1771–179* - *Reference: Z. R. Shi, C. Wang, F. Fang “AI for Social Good: A survey”, arXiv, 2020* ## AI for social good case studies, philosophy: ### 2. (Jan 28) Lecture 2: AI for social impact case studies and discussion [**Lecture video discussing AI and public safety** ](https://www.youtube.com/watch?v=O2su1u2AXG0&t=2s) [**Lecture 2 slides**](/file_url/115) ### 3. (Feb 2) Lecture 3: AI for social impact case studies and discussion [**Lecture video discussing AI for public health and conservation**](https://www.youtube.com/watch?v=Pcnhpz7oQAg&t=10s) [**Lecture 3 Slides**](/file_url/118) The goal of these two lectures is to explain my own group’s previous projects over the past 15 years in AI for Social Impact. I will discuss key projects, how they came about, what was the motivation, their progress, obstacles, lessons learned at the end. ***Optional readings:*** - *Andrew Perrault, Fei Fang, Arunesh Sinha, and Milind Tambe. 2020. “*[*AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline.*](https://teamcore.seas.harvard.edu/files/teamcore/files/ai_magazine_article.pdf)*” AI Magazine.* - *Bryan Wilder, Laura Onasch-Vera, Graham Diguiseppi, Robin Petering, Chyna Hill, Amulya Yadav, Eric Rice, and Milind Tambe. 2021. “*[*Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessness.*](https://teamcore.seas.harvard.edu/files/teamcore/files/aaai21_hiv.pdf)*” In AAAI Conference on Artificial Intelligence.* - *L. Xu, S. Gholami, S. Mc Carthy, B. Dilkina, A. Plumptre, M. Tambe, R. Singh, M. Nsubuga, J. Mabonga, M. Driciru, F. Wanyama, A. Rwetsiba, T. Okello, E. Enyel Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations In IEEE International Conference on Data Engineering (ICDE) , March 2020* - *Detlof von Winterfeldt R. Scott Farrow Richard S. John Jonathan Eyer Adam Z. Rose Heather Rosoff “*[*Assessing the Benefits and Costs of Homeland Security Research: A Risk‐Informed Methodology with Applications for the U.S. Coast Guard*](https://doi.org/10.1111/risa.13403)*” First published: 15 October 2019* **Background readings:** - D. Kempe, J. Kleinberg, and É. Tardos. Maximizing the Spread of Influence through a Social Network. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 137–146. ACM, 2003. - H. Kamarthi, P. Vijayan, B. Wilder, B. Ravindran,M. Tambe Influence maximization in unknown social networks: Learning Policies for Effective Graph Sampling In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May, 2020 ### 4. (Feb 4) Lecture 4: AI for Substance Abuse prevention (Invited lecture by Prof. Amulya Yadav) **Required readings** - Maryam Tabar, Heesoo Park, Stephanie Winkler, Dongwon Lee, Anamika Barman-Adhikari, Amulya Yadav “Identifying Homeless Youth At-Risk of Substance Use Disorder: Data-Driven Insights for Policymakers” KDD 2020 - Amulya Yadav, Roopali Singh, Nikolas Siapoutis, Anamika Barman-Adhikari, Yu Liang “Optimal and Non-Discriminative Rehabilitation Program Design for Opioid Addiction Among Homeless Youth” IJCAI 2020 - Zi-Yi Dou, Anamika Barman-Adhikari, Fei Fang, Amulya Yadav “Harnessing Social Media to Identify Homeless Youth At-Risk of Substance Use”, AAAI 2021 ***Optional Readings:*** - *Rice, E., Milburn, N. G., & Monro, W. (2011). Social networking technology, social network composition, and reductions in substance use among homeless adolescents. Prevention Science, 12(1), 80-88.* - *Thomas W Valente, Beth R Hoffman, Annamara Ritt-Olson, Kara Lichtman, and C Anderson Johnson. 2003. Effects of a social-network method for group assignment strategies on peer-led tobacco prevention programs in schools. American journal of public health 93, 11 (2003), 1837–1843.* ## Ethics of AI for Social Good ### 5. (Feb 9) Lecture 5: AI & Ethics (Embedded ethics) [**LECTURE 5 SLIDES**](/file_url/120) Ethical reasoning is an essential skill for today’s computer scientists. The Embedded EthiCS distributed pedagogy embeds philosophers directly into computer science courses to teach students how to think through the ethical and social implications of their work. - Thomas W Valente, Beth R Hoffman, Annamara Ritt-Olson, Kara Lichtman, and C Anderson Johnson. 2003. Effects of a social-network method for group assignment strategies on peer-led tobacco prevention programs in schools. American journal of public health 93, 11 (2003), 1837–1843. - A. Rahmattalabi, A. Yadav, B. Wilder, A. Fulginiti, P. Vayanos, E. Rice, M. Tambe Exploring Algorithmic Fairness in Robust Graph Covering Problems In Proceedings Conference on Neural Information Processing Systems (NeurIPS), December, 2019 ## Defining projects ### 6. (Feb 11) Lecture 6: Prof. Chris Golden: Public health and conservation - Sarah Whitmee, Andy Haines, Chris Beyrer, Frederick Boltz, Anthony G Capon, Braulio Ferreira de Souza Dias, Alex Ezeh, Howard Frumkin, Peng Gong, Peter Head, Richard Horton, Georgina M Mace, Robert Marten, Samuel S Myers, Sania Nishtar, Steven A Osofsky, Subhrendu K Pattanayak, Montira J Pongsiri, Cristina Romanelli, Agnes Soucat, Jeanette Vega, Derek Yach “Safeguarding human health in the Anthropocene epoch:report of The Rockefeller Foundation–Lancet Commission on planetary health” The Rockefeller Foundation–Lancet Commission on planetary health ### 7. (Feb 16) Lecture 7: WWF Invited lecture (Rohit Singh) [**WWF LECTURE SLIDES**](/file_url/123) Background on Tuesday's WWF lecturer, Rohit Singh. [https://wwf.panda.org/discover/knowledge\_hub/?356370/Life-on-the-Frontline-2019-A-global-survey-of-the-working-conditions-of-rangers (Links to an external site.)](https://wwf.panda.org/discover/knowledge_hub/?356370/Life-on-the-Frontline-2019-A-global-survey-of-the-working-conditions-of-rangers) [https://tigers.panda.org/reports/ (Links to an external site.)](https://tigers.panda.org/reports/) [https://wwf.panda.org/discover/our\_focus/wildlife\_practice/wildlife\_trade/wildlife\_crime\_initiative/](https://wwf.panda.org/discover/our_focus/wildlife_practice/wildlife_trade/wildlife_crime_initiative/) ### 8. (Feb 18) Lecture 8: AI and COVID-19: debate. Role of in the COVID-19 fight? [**Pointer to Michael Mina lecture at CRCS**](https://www.youtube.com/watch?v=6rjvSyCeT_A&t=79s) **Prof. Michael Mina (invited lecture)** - B. Wilder, M. Charpignon, J. Killian, H. Ou, A. Mate, S. Jabbari, A. Perrault, A. Desai, M. Tambe, M. Majumder “Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City” In Proceedings of the National Academy of Sciences (PNAS), 117(41): 25904-25910, 2020. - D. Larremore, B. Wilder, E. Lester, S. Shehata, J. Burke, J. Hay, M. Tambe, M. Mina, R. Parke “Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance” In Science Advances, eabd5393, 2020 ### 9. (Feb 23) Lecture 9: Discussion AI for Social Good; plus bandit models for health intervention Discussion (available on most streaming services): [**POVERTY INC**](https://www.amazon.com/Poverty-Inc-George-Ayittey/dp/B01AZ1CG1E) Papers: - A. Mate\*, J. Killian\*, H. Xu, A. Perrault, M. Tambe (\* equal contribution) Collapsing Bandits and Their Application to Public Health Interventions In Proceedings Conference on Neural Information Processing Systems (NeurIPS), December, 2020 - A. Biswas, G. Aggarwal, P. Varakantham, M. Tambe Learning Index Policies for Restless Bandits with Application to Maternal Healthcare In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2021 ***Optional:*** - *P. Whittle. Restless bandits: Activity allocation in a changing world. J. Appl. Probab., 25(A): 287–298, 1988.* - *R. R. Weber and G. Weiss. On an index policy for restless bandits. J. Appl. Probab., 27(3): 637–648, 1990.* ### 10. (Feb 25) Lecture 10: Implementation Science by Prof. Shoba Ramanadhan [**Shoba Ramanadhan Lecture Slides on implementation science**](/file_url/119) - [Mark S Bauer](https://pubmed.ncbi.nlm.nih.gov/?term=Bauer%20MS&cauthor_id=31036287), [JoAnn Kirchner](https://pubmed.ncbi.nlm.nih.gov/?term=Kirchner%20J&cauthor_id=31036287) "Implementation science: What is it and why should I care" Psychiatry Research - Mark S. Bauer, Laura Damschroder, Hildi Hagedorn, Jeffrey Smith & Amy M. Kilbourne “An introduction to implementation science for the non-specialist” BMC Psychology volume 3, Article number: 32 (2015) ## **STUDENT PAPER PRESENTATIONS** ### 11. (Mar 2) Lecture 11: Student paper presentation Paper: [Project RISE: Recognizing Industrial Smoke Emissions](https://arxiv.org/pdf/2005.06111.pdf) Appears at: AAAI 2021 (to appear), Special Track on AI for Social Impact RainBench: Towards Global Precipitation Forecasting from Satellite Imagery Appears at: Paper: [A Markov Decision Process Model for Socio-Economic Systems Impacted by Climate Change](http://proceedings.mlr.press/v119/shuvo20a/shuvo20a.pdf) Appears at: ICML 2020 Paper: [Security and privacy in Smart Farming: Challenges and Opportunities](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9003290&fbclid=IwAR0d26BUe1VUAFEqvKD6sNBqvhy0MOQHLp1g3Eh1-8b6Sq0nDTlo-MQFfHI) Appears at: IEEE Access 8 (2020) ### 12. (Mar 4) Lecture 12: Student presentations Paper: [Dual-Mandate Patrols: Multi-Armed Bandits for Green Security](https://arxiv.org/abs/2009.06560) Appears at: AAAI-21 Paper: [Protecting Geolocation Privacy of Photo Collections](https://arxiv.org/pdf/1912.02085.pdf) Appears at: AAAI-2020 Paper: [Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images](https://arxiv.org/pdf/2009.09283.pdf) Appears at: AAAI-21 - Special Track on AI for Social Impact Paper: [Weakly-Supervised Fine-Grained Event Recognition on Social Media Texts for Disaster Management](https://ojs.aaai.org//index.php/AAAI/article/view/5391) Appears at: AAAI 2020 Special Technical Track: AI for Social Impact ### 13. (Mar 9) Lecture 13: Student presentations Paper: [Predicting Patient Outcomes with Graph Representation Learning](https://www.dropbox.com/s/mzban2vfvwzm3u1/DLG_AAAI_21%20(1).pdf?dl=0) Appears at: AAAI 2021 Paper: [Personalizing ASR for Dysarthric and Accented Speech with Limited Data](https://www.isca-speech.org/archive/Interspeech_2019/pdfs/1427.pdf) Appears at: Interspeech 2019 Paper: [Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users](https://www.aaai.org/AAAI21Papers/AISI-8710.DoumbouyaM.pdf) Appears at: AAAI 2021 Special Track on AI for Social Impact ### 14. (Mar 11) Lecture 14: Midterm short presentations on project progress ### March 16: Wellness day no courses meet ## AI and sustainability: Learning to appreciate an interdisciplinary perspective ### 15. (Mar 18) Lecture 15:Invited Lecture on AI and Sustainability by Prof. Andrew Davies, Harvard EOB [**Andrew Davies Lecture Slides** ](/file_url/116) *Brodrick PG, Davies AB, and Asner GP. 8/2019. “*[*Uncovering ecological patterns with convolutional neural networks.Links to an external site.*](https://davieslab.oeb.harvard.edu/publications/uncovering-ecological-patterns-convolutional-neural-networks)*” Trends in Ecology and Evolution, 34, 8, Pp. 734-745.* [*Publisher's Version*](https://www.sciencedirect.com/science/article/pii/S0169534719300862) ## From Data to Deployment in AI4SG ### 16. (Mar 23) Lecture 16: Invited lecture by Bryan Wilder on measuring impact [**BRYAN WILDER SLIDES ON MEASURING IMPACT**](/file_url/122) ### 17. (Mar 25) Lecture 17: Discuss broader impacts of class projects M. Latonero “Opinion: AI For Good Is Often Bad” Wired November 2019 The conversation “AI algorithms intended to root out welfare fraud often end up punishing the poor instead”, Rawstory Feb 14, 2020 Beyond ‘AI for Social Good’ (AI4SG): social transformations—not tech-fixes—for health equity Cheryl Holzmeyer, Institute for Social Transformation, University of California, Santa Cruz, CA, USA E. Gibney “The battle for ethical AI at the world’s biggest machine-learning conference” Nature news, January 2020 ### 18. (Mar 30) Lecture 18: Invited Lecture by Phil Nelson, Google ## Fairness, Accountability, Transparency ### 19. (Apr 1) Lectures 19: Fairness in AI for Social Good [**FAIRNESS & AI FOR SOCIAL GOOD**](/file_url/121) A. Rahmattalabi, A. Yadav, B. Wilder, A. Fulginiti, P. Vayanos, E. Rice, M. Tambe Exploring Algorithmic Fairness in Robust Graph Covering Problems In Proceedings Conference on Neural Information Processing Systems (NeurIPS), December, 2019 A. Rahmattalabi, S. Jabbari, P. Vayanos, H. Lakkaraju, M. Tambe Fair Influence Maximization: a Welfare Optimization Approach In In AAAI conference on Artificial Intelligence (AAAI), February, 2021 ### 20. (Apr 6) Lecture 20: Question-answer session on second round of paper readings Paper: GLTR: [Statistical Detection and Visualization of Generated Text](https://arxiv.org/abs/1906.04043) Appears at: ACL 2019 Demo Track Paper: [A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning](https://ojs.aaai.org/index.php/AAAI/article/view/5376/5232) Appeared at: AAAI 2020 Paper: [Predicting Forest Fire Using Remote Sensing Data And Machine Learning](https://arxiv.org/pdf/2101.01975.pdf) Appeared at: AAAI 2021, Special Track on AI for Social Impact Paper: [Combining satellite imagery and machine learning to predict poverty](https://science.sciencemag.org/content/353/6301/790.abstract) Appears at: Science, Vol. 353, Issue 6301, 2016 Paper: [Inferring Nighttime Satellite Imagery from Human Mobility](https://arxiv.org/pdf/2003.07691.pdf) Appears at: AAAI 2020 Special Track on AI for Social Impact Paper: [Feature exploration for almost zero-resource ASR-free keyword spotting using a multilingual bottleneck extractor and correspondence autoencoders](https://www.isca-speech.org/archive/Interspeech_2019/pdfs/1665.pdf) Appears at: Interspeech 2019 Paper: [Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service](https://www.aaai.org/AAAI21Papers/AISI-8975.SivagnanamA.pdf) Appears at: AAAI 2021 Paper: [Spatio-Temporal Attention-Based Neural Network for Credit Card Fraud Detection](https://ojs.aaai.org/index.php/AAAI/article/download/5371/5227) Appears at: AAAI-2021, Special Track on AI for Social Impact Paper: [Characterizing soundscapes across diverse ecosystems using a universal acoustic feature set](https://www.pnas.org/content/pnas/117/29/17049.full.pdf) Appears at: PNAS 2020 Paper: [How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?](https://proceedings.neurips.cc/paper/2020/file/8e3308c853e47411c761429193511819-Paper.pdf) Appears at: NeurIPS 2020 ### 21. (Apr 8) Lecture 21: AI for Social Good and HCI 1. [Enabling Data-Driven API Design with Community Usage Data: A Need-Finding Study](http://glassmanlab.seas.harvard.edu/papers/Data-driven-API-CHI20.pdf) Tianyi Zhang, Björn Hartmann, Miryung Kim, and Elena Glassman. CHI 2020. 2. [Community power could boost confidence in vaccination programmes](https://hermansaksono.medium.com/community-power-can-boost-vaccine-uptake-5cf61a9b4949) RC Wurth, H Saksono Nature 589 (7841), 198 3. [Storywell: Designing for Family Fitness App Motivation by Using Social Rewards and Reflection](https://dl.acm.org/doi/abs/10.1145/3313831.3376686) Herman Saksono, Carmen Castaneda-Sceppa, Jessica Hoffman, Vivien Morris, Magy Seif El-Nasr, Andrea Parker. 2020. Storywell: Designing for Family Fitness App Motivation by Using Social Rewards and Reflection. In *CHI Conference on Human Factors in Computing Systems Proceedings (CHI 2020), May 4–9, 2019, Honolulu, HI, USA*. ACM, New York, NY, USA, 13 pages. ([PDF](https://scholar.harvard.edu/files/hsaksono/files/saksono_et_al_2020.pdf))3. 4. [Social technologies for digital wellbeing among marginalized communities](https://www.scholars.northwestern.edu/en/publications/social-technologies-for-digital-wellbeing-among-marginalized-comm) MA Devito, AM Walker, J Birnholtz, K Ringland, K Macapagal, A Kraus, ... Conference Companion Publication of the 2019 on Computer Supported ### 22. (Apr 13) Lecture 22: Interpretability in machine learning Invited Lecture by Dr. Hima Lakkaraju [**Hima Lakkaraju Lecture Slides on Explainability in ML**](/file_url/117) ### Apr 15: wellness day ### 23. (Apr 20) Lecture 23: Final project presentations ### 24. (Apr 22) Lecture 24: Final project presentations ### 25. (Apr 27) Lecture 25: Final project presentation